McMaster University

McMaster University

Faculty of
Health Sciences

McMaster researchers find genes can predict breast cancer response to chemotherapy

Published: May 10, 2012
John Hassell
John Hassell, professor in the Department of Biochemistry and Biomedical Sciences and director of the Centre for Functional Genomics

Scientists at McMaster University and Hamilton Health Sciences have discovered how genetic predictors can help personalize chemotherapy.

Although chemotherapy is the first line of defense against breast cancer, a patient's response to it is often variable and unpredictable.

The goal of personalized medicine in cancer treatment is to target therapy to the characteristics of the individual tumor. For example, Herceptin treatment is of most benefit to patients whose cancer is driven by HER2 and antiestrogens benefit patients whose breast cancer is hormonally driven. Gene signatures are increasingly available for different cancer types and can be used to predict patient prognosis.

The study from the McMaster scientists published in the medical journal BMC Medical Genomics shows that 'gene expression signatures' for TOP2A and β-tubulin can be used to predict the outcome of chemotherapy.

"Our results clearly demonstrate the practicality of using gene expression to personalize chemotherapy treatment for breast cancer patients," said project leader John Hassell, professor and director of McMaster's Centre for Functional Genomics. The study was performed by Greg Pond of the Department of Oncology and graduate student Robin Hallett.

"Identifying patients who will not benefit from a specific treatment means that they can be moved to a different treatment plan and the earlier, appropriate treatment is started, the more likely it is that the patients will benefit from it," said Hassell.

Researchers analyzed the expression of the enzyme TOP2A (DNA topoisomerase) and β-tubulin, which are the targets of commonly used chemotherapy drugs (anthracycline and taxane) in hundreds of breast tumors. Combining the results from the tumor samples analyses allowed the researchers to build gene expression 'signature' that predict the susceptibility of tumor cells to each chemotherapy and to the combination of each chemotherapy.

Both of the 'signatures' were separately able to predict which patients achieved a complete response (where invasive or metastatic cancer could no longer be detected) and together the two indices were even more accurate at predicting response to chemotherapy.

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